University of California Irvine Department of Economics

University of California Irvine
Department of Economics
Economics 122A: Applied Econometrics I
Prof. Safarzadeh
Assignment # 3
1. Convert the CPI variable to inflation. Define economic variables that would best explain inflation. Download data for those variables.2. Write a regression model explaining inflation.
3. Run a regression of the dependent variable (inflation) on the independent variables and estimate the model. Comment on the significance of the coefficients statistical output and the overall explaining power of the regression.
4. Check whether the classical regression assumptions are satisfied or not. Do proper corrections to meet the required conditions.
5. Find the estimated value of the dependent variable (y-hat). Plot the actual value of the dependent variable y estimated y (y-hat) and the residuals. Comment on the relationship among the variables.
6. Find the MAD MAPE and RMSE of the regression error.
7. Plot the error of the regression. Comment on the randomness of the error term. Test for the existence of outliers heteroscedasticity and/or serial correlation.
8. Make the necessary adjustments for heteroscedasticity or serial correlation.
9. Find the MAD MAPE and RMSE of the new regression error. Compare the MAD MAPE and RMSE to the MAD MAPE and SE in item 6.
10. Do a three period forecasting of the dependent variable assuming that independent variables will be increasing by 10% each period for the next three periods.
11. Test your dependent variable (inflation) for time trend. If trend exists detrend the variable.
12. Test your dependent variable (inflation) for the existence of seasonality. If seasonality exists deseasonalize the variable.
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